Image processing apparatus, program and image diagnostic apparatus

ABSTRACT

An image processing apparatus is provided. The image processing apparatus includes an acquiring device configured to acquire a typical pixel value corresponding to a noted region in an image, a calculating device configured to calculated index values of variances in pixel values in the noted region or in both the noted region and a region adjacent to the noted region, a first enhancement degree determination device configured to determine an enhancement degree according to the acquired typical pixel value and each of the calculated index values, and an image processing device configured to perform high-frequency enhancement processing on the noted region, based on the enhancement degree determined by the first enhancement degree determination device.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of Japanese Patent Application No.2011-040984 filed Feb. 26, 2011, which is hereby incorporated byreference in its entirety.

BACKGROUND OF THE INVENTION

The present invention relates to an image processing apparatus, aprogram and an image diagnostic apparatus which improve spatialresolution of an image.

Conventionally, in many X-ray CT (Computed Tomography) apparatuses, anarithmetic operation for overlay with a reconstruction function isperformed on projection data acquired by imaging, and back projectionprocessing is executed thereon to thereby reconstruct an X-ray CT image.

The quality of the X-ray CT image depends on the characteristic of thereconstruction function used in image reconstruction. Therefore, in eachX-ray CT apparatus, a plurality of types of reconstruction functionsrespectively different in the quality of the reconstructed image areprepared and provided to a user. There are prepared, for example, a lungfield function close to high spatial resolution so adjusted that ahigh-frequency component appears relatively strongly, a soft partfunction close to low noise so adjusted that a high-frequency componentappears relatively weakly, a standard function having an intermediateproperty between these, etc. The user properly uses these reconstructionfunctions according to diagnostic purposes, sections to be observed andthe like. See, for example, paragraphs [0021], [0029] and [0030] ofJapanese Patent Application Laid-Open No. 2004-073432.

On the other hand, when an image is reconstructed using a reconstructionfunction, spatial resolution and noise level in the reconstructed imageare in a trade off relationship with respect to each other. Therefore,when such a reconstruction function that the high-frequency componentappears extremely strongly is used in an attempt to enhance the spatialresolution to the maximum, an increase in noise becomes sharp so thatthe image may result in an image that does not withstand a practicaluse.

With this situation, in regard to the previously-prepared reconstructionfunction, the balance between spatial resolution and a noise level hasbeen adjusted within a range durable for practical use. Therefore, evenin the case of the reconstruction function close to the highest spatialresolution, potential spatial resolution of projection data has not yetbeen drawn to a maximal degree.

On the other hand, a section (e.g., auditory ossicles or the like)having a very fine structure even within the sections of a subject hasbeen desired at a higher spatial resolution. There has been room forfurther high spatial resolution. However, when using the reconstructionfunction adjusted such that an improvement in spatial resolution ispursued at random, and such that the high-frequency component appearsstrongly, noise is increased needlessly with respect to a region thatdoes not require such a high spatial resolution (e.g., a soft tissueregion), thus leading to an undesirable result.

With the foregoing in view, a process capable of making a furtherimprovement in spatial resolution for the region without increasingnoise needlessly is desired.

SUMMARY OF THE INVENTION

In a first aspect, an image processing apparatus is provided. The imageprocessing apparatus includes an acquiring device which acquires atypical pixel value corresponding to a noted region in an image, acalculating device which calculates index values of variances in pixelvalues in the noted region or the noted region and an adjacent regionthereof, a first enhancement degree determination device whichdetermines an enhancement degree according to the acquired typical pixelvalue and each of the calculated index values, and an image processingdevice which performs high-frequency enhancement processing on the notedregion, based on the enhancement degree determined by the firstenhancement degree determination device.

In a second aspect the image processing apparatus according to the firstaspect is provided, wherein the first enhancement degree determinationdevice specifies an enhancement degree corresponding to each of thecalculated index values, based on a first relation that indicates arelation between each of the index values of the variances and theenhancement degree and varies according to the typical pixel valuecorresponding to the noted region.

Incidentally, the first enhancement degree determination devicedetermines the first relation according to a typical pixel value. Itpartly includes such a case that a plurality of different typical pixelvalues and the same relation are associated with each other.

In a third aspect, the image processing apparatus according to thesecond aspect is provided, wherein in the first relation, each of indexvalues of variances included in a first range and a first enhancementdegree are associated with each other, each of index values of variancesincluded in a second range larger in index value than the first rangeand a second enhancement degree smaller than the first enhancementdegree are associated with each other, and each of index values ofvariances included in a third range larger in index value than thesecond range and a third enhancement degree larger than the secondenhancement degree are associated with each other.

In a fourth aspect, the image processing apparatus according to thethird aspect is provided, wherein the second range is a range of indexvalues of variances corresponding to the existence of an artifact.

In a fifth aspect, the image processing apparatus according to any oneof the first to fourth aspects is provided, further including secondenhancement determination device which determines an enhancement degreeaccording to the acquired typical pixel value, wherein the imageprocessing device performs high-frequency enhancement processing on thenoted region, based on the enhancement degree determined by the secondenhancement degree determination device.

In a sixth aspect, the image processing apparatus according to the fifthaspect is provided, wherein the second enhancement degree determinationdevice specifies an enhancement degree corresponding to the acquiredtypical pixel value, based on a second relation indicative of a relationbetween a typical pixel value corresponding to the noted region and anenhancement degree.

In a seventh aspect, the image processing apparatus according to thesixth aspect is provided, wherein in the second relation, a typicalpixel value included in a fourth range and a fourth enhancement degreeare associated with each other, a typical pixel value included in afifth range larger in pixel value than the fourth range and a fifthenhancement degree than the fourth enhancement degree are associatedwith each other, a typical pixel value included in a sixth range largerin pixel value than the fifth range and a sixth enhancement degreesmaller than the fifth enhancement degree are associated with eachother, and a typical pixel value included in a seventh range larger inpixel value than the sixth range and a seventh enhancement degree largerthan the sixth enhancement degree are associated with each other.

In an eighth aspect, the image processing apparatus according to theseventh aspect is provided, wherein the fourth range is a range of pixelvalues corresponding to the existence of air, and the sixth range is arange of pixel values corresponding to the existence of a soft tissue.

In a ninth aspect, the image processing apparatus according to any oneof the sixth to eighth aspects is provided, wherein the image is anX-ray CT image, and wherein the second enhancement degree determinationdevice determines an enhancement degree, based on the second relationthat varies according to a reconstruction function used inreconstruction of the X-ray CT image.

Incidentally, the second enhancement degree determination devicedetermines the second relation according to a reconstruction function.It partly includes such a case that a plurality of differentreconstruction functions and the same relation are associated with eachother.

In a tenth aspect, the image processing apparatus according to any oneof the first to ninth aspects is provided, further including thirdenhancement degree determination device which determines an enhancementdegree in such a manner that a larger value is acquired when an edge isnot detected by edge detection processing on the noted region or thenoted region and an adjacent region thereof rather than when the edge isdetected by the edge detection processing, wherein the image processingdevice performs high-frequency enhancement processing on the notedregion, based on the enhancement degree determined by the thirdenhancement degree determination device.

In an eleventh aspect, the image processing apparatus according to thetenth aspect is provided, wherein the edge detection processing is aprocess for determining that the edge has been detected where the numberof pixels, at which a difference between each of pixels values of pixelsin regions adjacent to the noted region and a typical pixel valuecorresponding to the noted region is greater than or equal to apredetermined threshold value, of the pixels in the regions adjacent tothe noted region, is greater than or equal to a predetermined number.

In a twelfth aspect, the image processing apparatus according to any oneof the first to eleventh aspects is provided, wherein the image is anX-ray CT image, wherein the image processing apparatus further includesfourth enhancement degree determination device which determines anenhancement degree in such a manner that a large value is acquired asthe distance from the center of reconstruction of the X-ray CT image tothe noted region increases, and wherein the image processing deviceperforms high-frequency enhancement processing on the noted region,based on the enhancement degree determined by the fourth enhancementdegree determination device.

In a thirteenth aspect, the image processing apparatus according to anyone of the fifth to twelfth aspects is provided, wherein the imageprocessing device performs high-frequency enhancement processing on thenoted region in accordance with enhancement degrees obtained byperforming multiplication, addition or weighted addition on a pluralityof the enhancement degrees determined.

In a fourteenth aspect, the image processing apparatus according to anyone of the first to thirteenth aspects is provided, wherein thehigh-frequency enhancement processing is sharpening filter processing.

In a fifteenth aspect, the image processing apparatus according to anyone of the first to fourteenth aspects is provided, wherein the typicalpixel value corresponding to the noted region is a pixel value of acentral pixel in the noted region, an average value of pixel values inthe noted region or both the noted region and the adjacent regionthereof, or a weighted average value thereof.

In a sixteenth aspect, the image processing apparatus according to anyone of the first to fifteenth aspects is provided, wherein each of theindex values of the variances is a variance or standard deviation ofpixel values in the noted region or the noted region and its adjacentregion.

In a seventeenth aspect, a program is provided. The program is forcausing a computer to function as an acquiring device which acquires atypical pixel value corresponding to a noted region in an image, acalculating device which calculates index values of variances in pixelvalues in the noted region or the noted region and an adjacent regionthereof, a first enhancement degree determination device whichdetermines an enhancement degree according to the acquired typical pixelvalue and each of the calculated index values, and an image processingdevice which performs high-frequency enhancement processing on the notedregion, based on the enhancement degree determined by the firstenhancement degree determination device.

In an eighteenth aspect, an image diagnostic apparatus is provided. Theimage diagnostic apparatus is equipped with an acquiring device whichacquires a typical pixel value corresponding to a noted region in animage, a calculating device which calculates index values of variancesin pixel values in the noted region or the noted region and an adjacentregion thereof, a first enhancement degree determination device whichdetermines an enhancement degree according to the acquired typical pixelvalue and each of the calculated index values, and an image processingdevice which performs high-frequency enhancement processing on the notedregion, based on the enhancement degree determined by the firstenhancement degree determination device.

In a nineteenth aspect, the image diagnostic apparatus according to theeighteenth aspect is provided, wherein X-ray CT imaging is conducted toreconstruct an image.

According to the aspects described above, spatial resolution can beimproved with respect to a region desirous of high spatial resolutionwithout increasing noise needlessly.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram schematically showing a configuration of an X-ray CTapparatus.

FIG. 2 is a diagram of a gantry as viewed from its side surface.

FIG. 3 is a functional block diagram of a portion related to adaptivehigh-frequency enhancement processing in the X-ray CT apparatus.

FIG. 4 is a flowchart of the adaptive high-frequency enhancementprocessing in the X-ray CT apparatus.

FIG. 5 is a diagram showing one example of a first relation indicativeof a correlation between a variance index value and an enhancementcoefficient.

FIG. 6 is a diagram illustrating one example of a second relationindicative of a correlation between a typical pixel value in a notedregion and an enhancement coefficient.

FIG. 7 shows one example of edge detection processing.

FIG. 8 is a diagram showing one example of a correlation between thedistance from an iso-center to a noted region and an enhancementcoefficient.

FIG. 9 is a diagram illustrating a sample image taken when the adaptivehigh-frequency enhancement processing is applied to an X-ray CT image ofauditory ossicles.

DETAILED DESCRIPTION OF THE INVENTION

Exemplary embodiments will be explained herein.

FIG. 1 is a diagram schematically showing a configuration of an X-ray CTapparatus.

As shown in FIG. 1, the present X-ray CT apparatus is equipped with agantry 2, a photographing table 4 and an operation console 6. The gantry2 has an X-ray tube 20. X-rays (not shown) emitted from the X-ray tube20 are formed to be an X-ray beam such as a sectorial fan beam, a conebeam or the like by means of an aperture 22 and applied to an X-raydetector 24.

The X-ray detector 24 has a plurality of X-ray detecting elementsarranged on a two-dimensional basis as viewed in an extending direction(channel direction) of the sectorial X-ray beam and its thicknessdirection (row direction).

A data acquisition section 26 is connected to the X-ray detector 24. Thedata acquisition section 26 acquires data detected by the individualX-ray detecting elements of the X-ray detector 24 as projection data.The application of the X-rays from the X-ray tube 20 is controlled by anX-ray controller 28. Incidentally, the relationship of connectionbetween the X-ray tube 20 and the X-ray controller 28 is omitted fromthe drawing.

Data about a tube voltage and current supplied to the X-ray tube 20 bythe X-ray controller 28 are acquired by the data acquisition section 26.Incidentally, the relationship of connection between the X-raycontroller 28 and the data acquisition section 26 is omitted from thedrawing.

The aperture 22 is controlled by an aperture controller 30.Incidentally, the relationship of connection between the aperture 22 andthe aperture controller 30 is omitted from the drawing.

A rotating section 34 of the gantry 2 is equipped with components fromthe X-ray tube 20 to the aperture controller 30. The rotation of therotating section 34 is controlled by a rotation controller 36.Incidentally, the relationship of connection between the rotatingsection 34 and the rotation controller 36 is omitted from the drawing.

The photographing table 4 carries an unillustrated subject in an X-rayirradiation space of the gantry 2 and carries the same out of the X-rayirradiation space.

The operation console 6 has a central processing unit 60. The centralprocessing unit 60 is configured by, for example, a computer or thelike. A control interface 62 is connected to the central processing unit60. The gantry 2 and the photographing table 4 are connected to thecontrol interface 62. The central processing unit 60 controls the gantry2 and the photographing table 4 through the control interface 62.

The data acquisition section 26, the X-ray controller 28, the aperturecontroller 30 and the rotation controller 36 in the gantry 2 arecontrolled through the control interface 62. Incidentally, theindividual connections between those parts and the control interface 62are omitted from the drawing.

A data acquisition buffer 64 is connected to the central processing unit60. The data acquisition section 26 of the gantry 2 is connected to thedata acquisition buffer 64. Data acquired by the data acquisitionsection 26 are inputted to the central processing unit 60 through thedata acquisition buffer 64.

The central processing unit 60 performs a scan planning process of anactual scan according to the operations by an operator. Also the centralprocessing unit 60 performs image reconstruction using projection dataof a plurality of views acquired through the data acquisition buffer 64.A three-dimensional image reconstruction process or the like by, forexample, a filtered back projection method is used in the imagereconstruction. The operator is able to select a reconstructionfunction, so-called kernel used in image reconstruction according to aregion or section to be observed and purposes. As the reconstructionfunction, a standard function, a soft part region function, a highresolution function and so on have been prepared.

The central processing unit 60 also performs adaptive high-frequencyenhancement processing to improve spatial resolution of an X-ray CTimage which is a reconstructed image.

A storage device 66 is connected to the central processing unit 60. Thestorage device 66 stores therein various data, reconstructed images anda program or the like for implementing the function of the present X-rayCT apparatus.

A display device 68 and an input device 70 are respectively connected tothe central processing unit 60. The display device 68 displays thereconstructed image and other information outputted from the centralprocessing unit 60. The input device 70 is operated by the operator andinputs various instructions, information and the like to the centralprocessing unit 60. The operator interactively operates the presentX-ray CT apparatus by use of the display device 68 and the input device70.

FIG. 2 is a diagram of the gantry 2 as viewed from its side surface. Asshown in FIG. 2, an X-ray radiated from the X-ray tube 20 is shaped tobe a fan-shaped X-ray beam 400 through the aperture 22 and applied tothe X-ray detector 24. The subject 8 placed on the photographing table 4with its body axis being allowed to intersect with the sectorial planeof such an X-ray beam 400, is carried in its corresponding X-rayirradiation space.

The X-ray irradiation space is shaped in space lying inside thecylindrical structure of the gantry 2. An image of the subject 8 slicedby the X-ray beam 400 is projected onto the X-ray detector 24. The X-raypenetrated through the subject 8 is detected by the X-ray detector 24.The thickness th of the X-ray beam 400 applied to the subject 8 isadjusted according to the degree of opening of the aperture 22.

The X-ray tube 20, the aperture 22 and the X-ray detector 24 are rotatedabout the body axis of the subject 8 while maintaining the mutualrelationship between them. Projection data about plural views per scan,e.g., 1000 views or so are acquired. The acquisition of the projectiondata is performed by a system of the X-ray detector 2, data acquisitionsection 26 and data acquisition buffer 64.

The central processing unit 60 performs image reconstruction of atomographic image, based on the projection data acquired by the dataacquisition buffer 64.

Incidentally, the direction of the body axis of the subject 8, i.e., thedirection of conveyance of the subject 8 on the photographing table 4 isassumed to be a z direction as shown in FIG. 2 herein. Further, thevertical direction is assumed to be a y direction, and the horizontaldirection perpendicular to the y and z directions is assumed to be an xdirection.

Thus, the adaptive high-frequency enhancement processing of the X-ray CTimage will now be explained.

FIG. 3 is a functional block diagram of a section related to theadaptive high-frequency enhancement processing of the X-ray CT image inthe X-ray CT apparatus. FIG. 4 is a flowchart of the adaptivehigh-frequency enhancement processing of the X-ray CT image.

As shown in FIG. 3, the present X-ray CT apparatus is equipped with animage acquisition unit 601, a pixel value acquisition unit 602, avariance index value calculating unit 603, a first enhancementcoefficient determination unit 604, a second enhancement coefficientdetermination unit 605, an edge detector 606, a third enhancementcoefficient determination unit 607, a distance measurement unit 608, afourth enhancement coefficient determination unit 609, an imageprocessor 610 and a controller 611.

The first enhancement coefficient determination unit 604 is equippedwith a first relation determination part 6041 and a first coefficientspecifying part 6042. The second enhancement coefficient determinationunit 605 is equipped with a second relation determination part 6051 anda second coefficient specifying part 6052. The image processor 610 isequipped with an enhancement degree determination part 6101 and ahigh-frequency enhancement processing part 6102.

Incidentally, the already-acquired projection data are assumed to havebeen stored in the storage device 66.

At step 51, the image acquisition unit 601 acquires an X-ray CT image Gwhich is a reconstructed image. Here, the image acquisition unit 601reads projection data P from the storage device 66 and performs imagereconstruction using a reconstruction function selected by a user, basedon the read projection data P to thereby acquire the corresponding X-rayCT image. As the reconstruction function, there are considered aplurality of types of reconstruction functions different in balancebetween spatial resolution and a noise level in the reconstructed image.As the reconstruction function, there are mentioned, for example, a lungfield function close to high spatial resolution, a soft part functionclose to a low noise level, a standard function having an intermediateproperty between these, etc.

At step S2, the controller 611 sets a noted region including one orplural pixels in the X-ray CT image G, and the pixel value acquisitionunit 602 acquires a typical pixel value C corresponding to the notedregion.

It is possible to roughly discriminate whether the noted region is anytissue of air, lung, mediastinal space/liver, bone/contrasted bloodvessels, etc., based on the typical pixel value C corresponding to thenoted region.

As the typical pixel value C corresponding to the noted region, thereare considered, for example, a pixel value of a central pixel in thenoted region, an average value of pixel values in the noted region orboth the noted region and its adjacent region or a weighted averagevalue thereof, etc. Herein, the noted region is assumed to be a regioncorresponding to one pixel. This will be called a noted pixel. Thetypical pixel value corresponding to the noted region is assumed to bethe average value of pixel values at the noted pixel and eight adjacentpixels lying orthogonally through the length and breadth of the notedpixel. Thus, information about each pixel value related to a sectionindicated by the noted region can be obtained while suppressing theeffect of noise.

At step S3, the variance index value calculating unit 603 calculates anindex value (hereinafter called a variance index value V) indicative ofthe degree of variance in the pixel values at the noted region and itsadjacent region.

It is possible to recognize the fineness of the structure of the notedregion, its noise level, etc., based on the variance index value V. Forexample, it is possible to roughly grasp whether the noted region is anyof (1) a soft part region of mediastinal space/liver or the like, (2) anartifact such as streak or the like and (3) so-called high-contrastregion of lung/bone/contrasted blood vessels or the like.

As the variance index value V, there can be considered, for example, avariance or standard deviation of pixel values in the noted region orthe noted region and its adjacent region, etc. Here, the variance indexvalue V is assumed to be a standard deviation of pixel values at apredetermined matrix region centering on a noted pixel, for example, aregion of 5×5 pixels.

At step S4, the first relation determination part 6041 determines afirst relation T1 indicative of a relationship between a variance indexvalue V and an enhancement coefficient H1, based on the typical pixelvalue C acquired at step S2. Incidentally, details on the first relationT1 and its determination method will be described later.

At step S5, the first coefficient specifying part 6042 specifies anenhancement coefficient H1 corresponding to the variance index value Vcalculated at step S3, by referring to the first relation T1 determinedat step S4.

Here, the term enhancement coefficient is a coefficient used todetermine or fix up the degree of enhancement of high-frequencyenhancement processing performed on the noted region. The enhancementcoefficient acts so as to relatively increase the degree of enhancementas the value thereof becomes large, and acts so as to relativelydecrease the degree of enhancement as the value thereof becomes small.

Incidentally, as the method for determining the first relation T1, thereis considered, for example, a method for dividing values each taken asthe typical pixel value C corresponding to the noted region into aplurality of ranges, storing candidates for the first relation T1 incorrespondence with one another every range and specifying the firstrelation T1 which is a candidate corresponding to the typical pixelvalue C acquired at step S2. For example, a predetermined function isprepared in which the typical pixel value C corresponding to the notedregion is defined as a parameter. Then the typical pixel value Cacquired at step S2 may be input to the predetermined function so as toderive the first function T1 therefrom.

One example of the first relation is shown in FIG. 5.

When the variance index value V is within a first range R1 relativelylow in the variance index value V in the first relation T1 according tothis example as shown in FIG. 5, there is a high possibility that thenoted region will be on a structure near a flat. Therefore, animprovement in spatial resolution and noise suppression are balanced toshare equally, so that the enhancement coefficient H1 is brought to 0.5or so (first enhancement coefficient) corresponding to an intermediatelevel. When the variance index value V is within a second range R2middle in the variance index value V, there is a high possibility thatthe noted region will be on a streak artifact. Therefore, theenhancement coefficient H1 is lowered to near zero indicative of theminimum level (second enhancement coefficient) so as to prevent theartifact from being enhanced. When the variance index value V is withina third range R3 relatively high in the variance index value V, there isa high possibility that the noted region will be on a fine structure.Therefore, the enhancement coefficient H1 is raised to near 1 indicativeof the maximum level (third enhancement coefficient) in such a mannerthat the structure can be grasped.

That is, the variance index value V included in the first range R1 andthe first enhancement coefficient are associated with each other. Also,the variance index value V included in the second range R2 larger invalue than the first range R1, and the second enhancement coefficientsmaller than the first enhancement coefficient correspond to each other.Further, the variance index value V included in the third range R3larger in value than the second range R2, and the third enhancementcoefficient larger than the second enhancement coefficient correspond toeach other.

Incidentally, now consider a balance between spatial resolution requiredfor each region of a reconstructed image and noise.

The balance between the spatial resolution required for each region ofthe reconstructed image and the noise differs depending on the type ofsection in each region even if variances in pixel values are the samedegree. For example, the noise suppression is relatively given priorityin the soft part region, whereas the high spatial resolution isrelatively given priority in the bone region.

In the present example, the first relation T1 is determined based on thetypical pixel value C corresponding to the noted region. Therefore, thetype of section in the noted region can be predicted a little from thetypical pixel value C corresponding to the noted region. Such anenhancement coefficient H1 that the balance between the spatialresolution and noise suitable for the noted region is obtained can bederived from the degree of variances in pixel values in the neighborhoodof the noted region in the form suitable for the predicted section.

Thus, the balance between the spatial resolution and noise suitable forthe noted region can meet a complicated and delicate request that occursdue to the combination of the type of section and the variances in pixelvalues.

At step S6, the second relation determination part 6051 determines asecond relation T2 indicative of the relationship between the typicalpixel value C and enhancement coefficient H2 corresponding to the notedregion according to a reconstruction function used in the imagereconstruction.

At step S7, the second coefficient specifying part 6052 specifies anenhancement coefficient H2 corresponding to the typical pixel value Cacquired at step S2 by referring to the second relation T2 determined atstep S6.

Incidentally, as the method of determining the second relation T2, therecan be considered, for example, a method of storing candidates for thesecond relation T2 in correspondence with one another respectively everytype of reconstruction function and specifying the second relation T2that is a candidate corresponding to a reconstruction function actuallyused in the image reconstruction of the X-ray CT image G.

One example of the second relation is shown in FIG. 6.

When the typical pixel value C corresponding to the noted region iswithin a fourth range R4 smallest in the value in the second relation T2according to this example as shown in FIG. 6, there is a highpossibility that the noted region will be air. Therefore, theenhancement coefficient H2 is lowered to near 0 corresponding to theminimum level (fourth enhancement coefficient) so as to prevent noisefrom increasing. When the typical pixel value C corresponding to thenoted region is within a fifth range R5 small in the value next, thereis a high possibility that the noted region will be a lung. Therefore,the enhancement coefficient H2 is raised up to near 1 corresponding tothe maximum level (fifth enhancement coefficient) in such a manner thatmicro points of calcification or the like can be grasped. When thetypical pixel value C corresponding to the noted region is within asixth range R6 small in the value next, there is a high possibility thatthe noted region will be mediastinal space, liver or the like.Therefore, the enhancement coefficient H2 is lowered to near 0corresponding to the minimum level (sixth enhancement coefficient) so asto prevent noise from increasing. When the typical pixel value Ccorresponding to the noted region is within a seventh range R7 small inthe value next, there is a high possibility that the noted region willbe bones, contrasted blood vessels or the like. Therefore, theenhancement coefficient H2 is raised up to near 1 corresponding to themaximum level (seventh enhancement coefficient) in such a manner that afine structure such as auditory ossicles, calcification in blood vesselsor the like can be grasped.

That is, the pixel value included in the fourth range R4 and the fourthenhancement coefficient correspond to each other. The pixel valueincluded in the fifth range R5 larger in pixel value than the fourthrange R4 and the fifth enhancement coefficient larger than the fourthenhancement coefficient are associated with each other. The pixel valueincluded in the sixth range R6 larger than the fifth range R5 in pixelvalue, and the sixth enhancement coefficient smaller than the fifthenhancement coefficient correspond to each other. The pixel valueincluded in the seventh range R7 larger than the sixth range R6 in pixelvalue, and the seventh enhancement coefficient larger than the sixthenhancement coefficient correspond to each other.

Incidentally, the states of the spatial resolution and noise in thereconstructed image differ greatly according to the reconstructionfunction used in the image reconstruction. Since the second relation T2is changed depending on the reconstruction function used in the imagereconstruction in the present example, the second relation T2 to bereferred can be determined in consideration of the difference in thestate therebetween.

At step S8, the edge detector 606 performs edge detection processing inthe noted region and its adjacent region.

At step S9, the third enhancement coefficient determination unit 607determines an enhancement coefficient H3 in such a manner that its valuebecomes larger where no edge is detected rather than where the edge isdetected by the edge detection processing.

It is thus possible to derive the enhancement coefficient H3 capable ofpreventing the occurrence of overshoot or undershoot due to theexcessive enhancement of an edge portion at which the pixel valuechanges suddenly.

One example of the edge detection processing is shown in FIG. 7. As theedge detection processing, there is considered as shown in FIG. 7, forexample, a process for, when a change in pixel value in a predetermineddirection is viewed in a predetermined matrix region centering on anoted pixel, e.g., a region of 5×5 pixels, determining an edge to havebeen detected if the difference in pixel value between adjacent pixelsis greater than or equal to a predetermined threshold value. There isconsidered, for example, a process for determining an edge to have beendetected when the number of pixels, at which the difference in pixelvalue with respect to the noted pixel is greater than or equal to thepredetermined threshold value, of the pixels included in thepredetermined matrix region centering on the noted pixel is greater thanor equal to a predetermined number.

At step S10, the distance measurement unit 608 measures a distance Dfrom the reconstruction center, i.e., iso-center in the reconstructedimage to the noted region.

At step S11, the fourth enhancement coefficient determination unit 609determines an enhancement coefficient H4 in such a manner that its valuebecomes large as the distance D measured at step S10 increases.

One example of the relationship between the distance D from theiso-center to the noted region and the enhancement coefficient H4 isshown in FIG. 8. In this example, the enhancement coefficient H4 is 0 ina range in which the distance D is from 0 cm to 20 cm. The enhancementcoefficient H4 increases gradually in a range in which the distance D isfrom 20 cm to 45 cm. The enhancement coefficient H4 becomes 1 when thedistance D is greater than 45 cm.

It is known that the spatial resolution becomes low with distance fromthe iso-center in the X-ray CT image corresponding to the reconstructedimage. It is thus possible to derive an enhancement coefficient capableof suppressing a reduction in the spatial resolution at the peripheralportion of the reconstructed image.

At step S12, the enhancement degree determination part 6101 performsmultiplication, addition or weighted addition or the like on all thedetermined enhancement coefficients H1 through H4 to thereby determinean enhancement degree HA.

At step S13, high-frequency enhancement processing is performed on thenoted region, based on the enhancement degree HA determined at step S12.

As the high-frequency enhancement processing, there can be considered,for example, sharpening filter processing using a weighted coefficientmatrix, which is known to date.

Thus, the high-frequency enhancement processing on which the effect ofcorrecting the spatial resolution and noise held in each enhancementcoefficient is reflected is performed on the noted region.

At step S14, the controller 613 determines whether or not a region to beset as the noted region lies elsewhere. If it exists elsewhere, theflowchart returns to step S2, where a new noted region is set and theprocessing is continued. If it does not exist elsewhere, the processingis terminated.

FIG. 9 shows a sample image taken when the adaptive high-frequencyenhancement processing is applied to an X-ray CT image of auditoryossicles. The left image is an original image G, the central image is aprocessed image G′, and the right image is a difference image (G′-G)between the processed image and the original image. In the processedimage G′, the enhancement of high-frequency components is sufficientlyperformed on a high contrast region for the bones so that high spatialresolution is obtained. It is however found that the enhancement ofhigh-frequency components is hardly performed on a soft part region anda region having a relatively flat structure of a bone part and hence anincrease in noise is suppressed.

According to the embodiments described herein, the enhancement degree ofthe high-frequency enhancement processing performed on the noted regioncan be changed according to the combined condition of both the pixelvalue related to the noted region and the degree of variance in thepixel value.

Therefore, the type of section in the noted region and the state of itsstructure can first be discriminated in pieces. For example, the finediscrimination of a fine structure of each of the soft part region andthe bone/contrasted blood vessels, a structure relatively flat, astructure like an artifact, etc. can be performed on the noted region inaddition to the discrimination of air, lungs and the like.

It is possible to perform the high-frequency enhancement processing onthe noted region with the suitable enhancement degree corresponding tothe result of discrimination. For example, when it is considered thatthe noted region is a bone region judging from each pixel value but hasa relatively flat structure judging from the degree of variances inpixel values, it is possible to suppress an increase in noise withoutthe enhancement of the high-frequency components. Further, for example,even when the degree of variances in pixel values in a region consideredto be an artifact changes depending on the type of substance or section,it is also possible to accurately determine whether the noted region isan artifact region and suppress an increase in noise without theenhancement of each high-frequency component if it is found to be theartifact region.

As a result, it is possible to suppress an increase in unnecessary noisewithout the enhancement of each high-frequency component with respect toa region in which noise suppression should be given priority and, in themean time, to improve spatial resolution while enhancing eachhigh-frequency component with respect to a region really desirous ofhigh spatial resolution.

The embodiments described herein enable a delicate correction thatcannot be obtained by the conventional method. For example, even if anenhancement coefficient determined according to only a pixel value andan enhancement coefficient determined according to only a variance indexvalue of a pixel value are combined together to generate a newenhancement coefficient, enhancement coefficients respectivelydetermined in another aspect may repel each other. It is difficult toperform such a delicate correction as described above.

Incidentally, the present invention is not limited to the embodimentsspecifically described herein, but may be added and modified in variousways within the scope not departing from the gist thereof.

For example, the combination and order of the processes for determiningthe enhancement coefficient are not limited to the embodiments describedherein. A process based on several aspects may be omitted, a processbased on another aspect may be added, and the order may be changed. Theconcrete contents of the process for determining the enhancementcoefficient are not limited to the embodiments described herein.

Although in the embodiments described herein, for example, therespective enhancement coefficients are integrated to determine oneenhancement degree, and the high-frequency enhancement processing isperformed based on the enhancement degree, the high-frequencyenhancement processing based on the enhancement coefficients maysequentially be performed for every enhancement coefficient.

An image processing apparatus having a functional block related to theabove image processing, a program for causing a computer to function assuch an image processing apparatus, and another image diagnosticapparatus equipped with such an image processing apparatus are merelyexemplary. The image diagnostic could include, for example, a PET-CTapparatus, an Angio-CT apparatus, radiation therapy equipment with a CTfunction, etc.

1. An image processing apparatus comprising: an acquiring deviceconfigured to acquire a typical pixel value corresponding to a notedregion in an image; a calculating device configured to calculated indexvalues of variances in pixel values in the noted region or in both thenoted region and a region adjacent to the noted region; a firstenhancement degree determination device configured to determine anenhancement degree according to the acquired typical pixel value andeach of the calculated index values; and an image processing deviceconfigured to perform high-frequency enhancement processing on the notedregion, based on the enhancement degree determined by the firstenhancement degree determination device.
 2. The image processingapparatus according to claim 1, wherein the first enhancement degreedetermination device is configured to specify an enhancement degreecorresponding to each of the calculated index values, the enhancementdegree specified based on a first relation between each of the indexvalues of the variances and the enhancement degree, wherein the firstrelation is based on the typical pixel value corresponding to the notedregion.
 3. The image processing apparatus according to claim 2, whereinin the first relation, each of the index values of the variancesincluded in a first range are associated with a first enhancementdegree, each of the index values of the variances included in a secondrange that is larger in index value than the first range are associatedwith a second enhancement degree that is smaller than the firstenhancement degree, and each of the index values of the variancesincluded in a third range that is larger in index value than the secondrange are associated with a third enhancement degree that is larger thanthe second enhancement degree.
 4. The image processing apparatusaccording to claim 3, wherein the second range is a range of indexvalues of variances corresponding to the existence of an artifact. 5.The image processing apparatus according to claim 1, further including asecond enhancement determination device configured to determine anenhancement degree according to the acquired typical pixel value,wherein the image processing device is configured to performhigh-frequency enhancement processing on the noted region, based on theenhancement degree determined by the second enhancement degreedetermination device.
 6. The image processing apparatus according toclaim 5, wherein the second enhancement degree determination device isconfigured to specify an enhancement degree corresponding to theacquired typical pixel value, the enhancement degree specified based ona second relation between a typical pixel value corresponding to thenoted region and an enhancement degree.
 7. The image processingapparatus according to claim 6, wherein in the second relation, atypical pixel value included in a fourth range is associated with afourth enhancement degree, a typical pixel value included in a fifthrange that is larger in pixel value than the fourth range is associatedwith a fifth enhancement degree that is larger than the fourthenhancement degree, a typical pixel value included in a sixth range thatis larger in pixel value than the fifth range is associated with a sixthenhancement degree that is smaller than the fifth enhancement degree,and a typical pixel value included in a seventh range that is larger inpixel value than the sixth range is associated with a seventhenhancement degree that is larger than the sixth enhancement degree. 8.The image processing apparatus according to claim 7, wherein the fourthrange is a range of pixel values corresponding to the existence of air,and the sixth range is a range of pixel values corresponding to theexistence of a soft tissue.
 9. The image processing apparatus accordingto claim 6, wherein the image is an X-ray CT image, and wherein thesecond enhancement degree determination device is configured todetermine an enhancement degree, based on the second relation, whereinthe second relation is based on a reconstruction function used inreconstruction of the X-ray CT image.
 10. The image processing apparatusaccording to claim 1, further including a third enhancement degreedetermination device configured to determine an enhancement degree suchthat a larger value is acquired when an edge is not detected by edgedetection processing on the noted region or the noted region and aregion adjacent to the noted region, and a smaller value is acquiredwhen the edge is detected by the edge detection processing, wherein theimage processing device is configured to perform high-frequencyenhancement processing on the noted region, based on the enhancementdegree determined by the third enhancement degree determination device.11. The image processing apparatus according to claim 10, wherein theedge detection processing is a process configured to: identify a numberof pixels in regions adjacent to the noted region that have a differencebetween their respective pixel values and a typical pixel valuecorresponding to the noted region that is greater than or equal to apredetermined threshold difference; and detect an edge when theidentified number of pixels is greater than or equal to a predeterminednumber.
 12. The image processing apparatus according to claim 1, whereinthe image is an X-ray CT image, wherein the image processing apparatusfurther includes a fourth enhancement degree determination deviceconfigured to determine an enhancement degree such that larger valuesare acquired as the distance from a center of reconstruction of theX-ray CT image to the noted region increases, and wherein the imageprocessing device is configured to perform high-frequency enhancementprocessing on the noted region, based on the enhancement degreedetermined by the fourth enhancement degree determination device. 13.The image processing apparatus according to claim 5, wherein the imageprocessing device is configured to perform high-frequency enhancementprocessing on the noted region based on one of multiplication, addition,and weighted addition of a plurality of the enhancement degreesdetermined.
 14. The image processing apparatus according to claim 1,wherein the high-frequency enhancement processing is sharpening filterprocessing.
 15. The image processing apparatus according to claim 1,wherein the typical pixel value corresponding to the noted region is oneof a pixel value of a central pixel in the noted region, an averagevalue of pixel values in the noted region or both the noted region andthe adjacent region, or a weighted average value of the pixel value ofthe central pixel and the average value.
 16. The image processingapparatus according to claim 1, wherein each of the index values of thevariances is a one of a variance and standard deviation of pixel valuesin the noted region or pixel values in the noted region and the adjacentregion.
 17. A program configured to cause a computer to function as: anacquiring device configured to acquire a typical pixel valuecorresponding to a noted region in an image; a calculating deviceconfigured to calculate index values of variances in pixel values in thenoted region or in both the noted region and a region adjacent to thenoted region; a first enhancement degree determination device configuredto determine an enhancement degree according to the acquired typicalpixel value and each of the calculated index values; and an imageprocessing device configured to perform high-frequency enhancementprocessing on the noted region, based on the enhancement degreedetermined by the first enhancement degree determination device.
 18. Animage diagnostic apparatus comprising: an acquiring device configured toacquire a typical pixel value corresponding to a noted region in animage; a calculating device configured to calculate index values ofvariances in pixel values in the noted region or in both the notedregion and a region adjacent to the noted region; a first enhancementdegree determination device configured to determine an enhancementdegree according to the acquired typical pixel value and each of thecalculated index values; and an image processing device configured toperform high-frequency enhancement processing on the noted region, basedon the enhancement degree determined by the first enhancement degreedetermination device.
 19. The image diagnostic apparatus according toclaim 18, wherein X-ray CT imaging is conducted to reconstruct theimage.
 20. The image diagnostic apparatus according to claim 18, whereinthe first enhancement degree determination device is configured tospecify an enhancement degree corresponding to each of the calculatedindex values, the enhancement degree specified based on a first relationbetween each of the index values of the variances and the enhancementdegree, wherein the first relation is based on the typical pixel valuecorresponding to the noted region.